Introduction

My thesis is looking at the diversity within a small-bodied freshwater fish species, the Blackside Snubnose Darter (Etheostoma duryi).

Figure 1. Etheostoma duryi male in breeding condition

While this species is conservative with meristic variation, we can investigate a suite of traits to assess some diversity.

Figure 2. Guide for collecting meristic data on fishes

Below are some analyses that can be done just with the data collected thus far.

Analyses with Meristics

We have data for 656 Etheostoma duryi specimens that were housed in museums.

Table 1. A summary kable displaying minimum and maximum lateral line scales for each locality
Locality n minimum maximum
81 43 55
Duck 158 40 55
Elk 164 NA NA
Elk 10 41 46
Emory 2 48 52
Flint 17 43 52
Lower TN 113 38 60
Middle TN 38 40 53
Paint Rock 14 40 51
Sequatchie 41 42 50
Shoal 18 40 56
Frequency table showing modal values for pectoral fin rays per locality.
11 12 13 14 15 16
0 0 35 36 10 0
Duck 0 7 46 79 25 1
Elk 0 10 63 56 26 9
Elk 0 1 4 5 0 0
Emory 0 1 1 0 0 0
Flint 1 3 7 6 0 0
Lower TN 0 14 50 45 4 0
Middle TN 0 2 20 13 2 1
Paint Rock 0 1 8 4 1 0
Sequatchie 0 6 25 8 1 0
Shoal 0 2 4 12 0 0
Frequency table showing modal values for dorsal fin spines per locality
9 10 11 12 13
2 15 60 4 0
Duck 1 37 91 27 2
Elk 4 43 99 18 0
Elk 0 2 5 3 0
Emory 0 1 1 0 0
Flint 0 3 10 4 0
Lower TN 1 22 58 31 1
Middle TN 1 16 15 5 1
Paint Rock 0 4 8 2 0
Sequatchie 0 7 32 2 0
Shoal 0 1 4 13 0
Frequency table showing modal values for lateral line scales per locality
38 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 60
0 0 0 0 1 1 5 10 7 8 12 11 11 7 2 5 1 0 0
Duck 0 1 2 5 3 10 12 25 18 18 20 12 16 6 7 2 1 0 0
Elk 0 0 3 7 8 10 20 14 23 20 21 17 9 5 3 1 0 1 0
Elk 0 0 2 3 1 1 2 1 0 0 0 0 0 0 0 0 0 0 0
Emory 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0
Flint 0 0 0 0 3 2 2 2 3 2 2 0 0 1 0 0 0 0 0
Lower TN 1 0 1 3 2 6 7 9 12 19 17 18 7 6 2 1 1 0 1
Middle TN 0 1 1 1 1 1 3 7 5 7 4 3 2 1 1 0 0 0 0
Paint Rock 0 1 0 0 0 0 0 3 3 2 3 1 1 0 0 0 0 0 0
Sequatchie 0 0 0 3 4 3 5 7 5 4 6 4 0 0 0 0 0 0 0
Shoal 0 1 1 0 1 0 4 2 1 1 3 0 1 1 1 0 0 1 0 
ggplot(counts, aes(x = Locality, y = Lateral.Line))+
  geom_boxplot()

ggsave('LocalityvsLateralLine.png')
## Saving 7 x 5 in image
ggplot(counts, aes(x = SL..mm., y = Lateral.Line, colour = Locality))+  geom_point()

ggsave('LocalityvsSLvsLL.png') 
## Saving 7 x 5 in image

Testing Models

Looking at somewhat random models

plot(Lateral.Line ~ SL..mm., data = counts)
sizeLLmodel <- lm(Lateral.Line ~ SL..mm., data = counts)
abline(sizeLLmodel)

anova(sizeLLmodel)
## Analysis of Variance Table
## 
## Response: Lateral.Line
##            Df Sum Sq Mean Sq F value  Pr(>F)    
## SL..mm.     1  177.5 177.514  19.944 9.4e-06 ***
## Residuals 652 5803.3   8.901                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
plot(Caudal.Peduncle ~ SL..mm., data = counts)

sizeCPmodel <- lm(Caudal.Peduncle ~ SL..mm., data = counts)
anova(sizeCPmodel)
## Analysis of Variance Table
## 
## Response: Caudal.Peduncle
##            Df Sum Sq Mean Sq F value    Pr(>F)    
## SL..mm.     1  20.29 20.2850  14.446 0.0001577 ***
## Residuals 652 915.53  1.4042                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1